Bayesian Network
A Simple Gibbs Sampler for Learning Bayesian Network Structure

Vahid Rezaei Tabar

Volume 1, Issue 2 , June 2023, , Pages 87-97

  The aim of this paper is to learn a Bayesian network structure for discrete variables. For this purpose, we introduce a Gibbs sampler method. Each sample represents a Bayesian network. Thus, in the process of Gibbs sampling, we obtain a set of Bayesian networks. For achieving a single graph that represents ...  Read More

A Bayesian Semiparametric Random Effect Model for Meta-Regression

Ehsan Ormoz

Volume 1, Issue 2 , June 2023, , Pages 205-223

  In this paper, we will introduce a Bayesian semiparametric model concerned with both constant and coefficients. In Meta-Analysis or Meta-Regression, we usually use a parametric family. However, lately the increasing tendency to use Bayesian nonparametric and semiparametric models, entered this area too. ...  Read More